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توسعۀ مدل عامل‌بنیان به منظور شبیه‌سازی رفتار بهره‌برداران بخش کشاورزی در مدیریت آب و اراضی | ||
| اکوهیدرولوژی | ||
| مقاله 12، دوره 7، شماره 2، تیر 1399، صفحه 421-435 اصل مقاله (878.1 K) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ije.2020.286216.1183 | ||
| نویسندگان | ||
| سیده شیما پورعلی حسین1؛ مجید دلاور* 2؛ امینه قربانی3؛ پیتر فان درزاخ4؛ سعید مرید5؛ عنایت عباسی6 | ||
| 1دانشجوی دکتری گروه مهندسی منابع آب، دانشکدۀ کشاورزی، دانشگاه تربیت مدرس، تهران، ایران | ||
| 2استادیار گروه مهندسی منابع آب، دانشکدۀ کشاورزی، دانشگاه تربیت مدرس، تهران، ایران | ||
| 3استادیار گروه سیستمهای مهندسی و خدمات، دانشکدۀ تکنولوژی، سیاست و مدیریت، دانشگاه تکنولوژی دلفت، دلفت، هلند | ||
| 4استاد گروه مدیریت آب، دانشکدۀ سیستمهای یکپارچۀ آب و حکمرانی، مؤسسۀ تحقیقات آب یونسکو، دلفت، هلند، استاد گروه مدیریت آب، دانشکدۀ مهندسی عمران، دانشگاه تکنولوژی دلفت، دلفت، هلند | ||
| 5استاد گروه مهندسی منابع آب، دانشکدۀ کشاورزی، دانشگاه تربیت مدرس، تهران، ایران | ||
| 6دانشیار گروه ترویج و آموزش کشاورزی، دانشکدۀ کشاورزی، دانشگاه تربیت مدرس، تهران، ایران | ||
| چکیده | ||
| با توجه به تأثیرات اجتماعی و تفاوتهای موجود در بخشهای مختلف سیستم، در نظر نگرفتن ویژگیها و رفتارهای اجتماعی بهره‌برداران و توجه صرف به مدیریت همگن و بالا-پایین، رویکرد موفقی در مدیریت پایدار منابع آب نخواهد بود. مدلسازی عامل‌بنیان (Agent-Based Model)، رویکرد تقریباً نوینی است که به دلیل لحاظ کردن این تفاوتها، در زمینۀ مدیریت منابع آب و اراضی امکانات مفیدی را در تحلیل رفتارهای اجتماعی و مدیریت مؤثر و پایدار منابع ارائه میکند. در تحقیق حاضر، سعی شده است تا ویژگیهای رفتاری و محیطی عوامل تصمیمگیرنده در خصوص بهرهبرداری آب در بخش کشاورزی، با ارائۀ یک چارچوب مفهومی و توسعۀ مدل عامل‌بنیان شبیه‌سازی شود. به این منظور، برای تدوین مدل مفهومی و فراهم کردن امکان شبیه‌سازی و تحلیل رفتاری عوامل بهرهبردار (برای تعیین الگوی کشت، روش آبیاری و به تبع آن، میزان آب برداشتی در سه سطح دولت، سازمانی و کشاورزان)، از چارچوب تحلیل و توسعۀ نهادی MAIA استفاده شده است. بر این اساس، مدل عامل‌بنیان در یک حوضۀ پایلوت در کشور (حوضۀ آبخیز حبلهرود) کدنویسی، صحتسنجی، واسنجی و اعتبارسنجی شد. این مدل، در شبیه‌سازی وضعیت حوضه شامل تغییرات جریان آب سطحی، الگو و سطح اراضی زراعی و باغی و برداشت از منابع آب زیرزمینی در دورۀ تاریخی 1982ـ 2013 عملکرد مناسبی داشته است. درضمن، برای بررسی تأثیر سیاستهای حفاظتی دستگاههای دولتی بر شرایط حوضۀ آبخیز، سناریوهای دریافت و افزایش آببها در مدل تعریف شده و نتایج بررسی شد (کاهش برداشت آب بین 8 تا 32 میلیونمترمکعب صرفهجویی در برداشت آب تحت سناریوهای هزار تا دههزار ریال تعرفۀ آببها). | ||
| کلیدواژه‌ها | ||
| تصمیمگیری؛ حوضۀ آبخیز حبلهرود؛ چارچوب MAIA؛ Agent-Based Model | ||
| عنوان مقاله [English] | ||
| Development of an Agent-Based Model to simulate the behavior of Agricultural Users in Water and Land Management | ||
| نویسندگان [English] | ||
| Seyedeh Shima Pooralihossein1؛ Majid Delavar2؛ Amineh Ghorbani3؛ Pieter Van Derzaag4؛ Saeed Morid5؛ Enayat Abbasi6 | ||
| 1PhD Student, Water Resources Engineering Group, Agriculture Dept., Tarbiat Modares University, Tehran, Iran | ||
| 2Assistant Professor, Water Resources Engineering Group, Agriculture Dept., Tarbiat Modares University, Tehran, Iran | ||
| 3Assistant Professor, Engineering Systems and Services Group, Technology, Policy and Management Dept., Delft University of Technology, Delft, Netherlands | ||
| 4Professor, Water Management Group, Integrated Water Systems and Governance Dept., IHE Delft Institute for Water Education, Delft, Netherlands Professor, Water Management Group, Civil Engineering Dept., Delft University of Technology, | ||
| 5Professor, Water Resources Engineering Group, Agriculture Dept., Tarbiat Modares University, Tehran, Iran | ||
| 6Associate Professor, Agricultural Promotion and Education Group, Agriculture Dept., Tarbiat Modares University, Tehran, Iran | ||
| چکیده [English] | ||
| Since there are various social factors and differences between different sectors of the system, ignoring water users’ attributes and their social behavior as well as considering only the homogeneous and up-down management scheme, would not be a successful approach in sustainable water management. Agent-Based Modeling is a relatively new approach that provides helpful tools to simulate social behaviors in sustainable water management. In this study, the agriculture sector’s water use is simulated using a conceptual framework and an Agent-Based Model to study the behavior of the decision-making agents. Therefore, to prepare the conceptual model and to simulate and analyze the social behavior of water users (in three decision levels of the Government, local organizations, and farmers) to decide on the cropping pattern, the irrigation method, and consequently the water withdrawal volume, the MAIA framework has been applied. In this regard, the Agent-Based Model for a pilot study area (the Hablehroud River basin, Iran) was coded, verified, calibrated, and validated. This model had a good performance in simulating the basin’s conditions, including cropping patterns and areas, and therefore the stream flow and groundwater use. Furthermore, to assess the impacts of the government’s water conservation policies on the hydrologic conditions, different scenarios of taking and increasing water costs were defined and modeled (one to ten thousand IRR per cm of water use led to a decrease in the total water withdrawals in the range of 8-32 million cubic meters per year). | ||
| کلیدواژه‌ها [English] | ||
| Agent-Based Model, MAIA framework, Decision-making, the Hablehroud River basin | ||
| مراجع | ||
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[1]. Maes D, Van Passel S. An agent-based model of farmer behaviour to explain the limited adaptability of Flemish agriculture. Environmental Innovation and Societal Transitions. 2017 Mar 1;22:63-77. [2]. Guillem EE, Murray-Rust D, Robinson DT, Barnes A, Rounsevell MD. Modelling farmer decision-making to anticipate tradeoffs between provisioning ecosystem services and biodiversity. Agricultural Systems. 2015 Jul 1;137:12-23. [3]. Bringezu S, Schütz H, Pengue W, O'Brien M, Garcia F, Sims R, et al. Assessing global land use: balancing consumption with sustainable supply. United Nations Environment Programme; 2014. [4]. Daloğlu I, Nassauer JI, Riolo RL, Scavia D. Development of a farmer typology of agricultural conservation behavior in the American Corn Belt. Agricultural Systems. 2014 Jul 1;129:93-102. [5]. Kremmydas D, Athanasiadis IN, Rozakis S. A review of agent based modeling for agricultural policy evaluation. Agricultural systems. 2018 Jul 1;164:95-106. [6]. Qalehban Tokmehdash M, Taheri Tizro A, Zare Abyaneh H. Agent-Based models in simulating the stakeholders’ behavior in water resources management. Water and Sustainable Development. 2015;2(1): 87-94. [Persian] [7]. Akhbari M, Grigg NS. A framework for an agent-based model to manage water resources conflicts. Water resources management. 2013 Sep 1;27(11):4039-52. [8]. Berglund EZ. Using agent-based modeling for water resources planning and management. Journal of Water Resources Planning and Management. 2015 May 12;141(11):04015025. [9]. Marvuglia A, Rege S, Gutierrez TN, Vanni L, Stilmant D, Benetto E. A return on experience from the application of agent-based simulations coupled with life cycle assessment to model agricultural processes. Journal of cleaner production. 2017 Jan 20;142:1539-51. [10]. Malawska A, Topping CJ. Evaluating the role of behavioral factors and practical constraints in the performance of an agent-based model of farmer decision making. Agricultural Systems. 2016 Mar 1;143:136-46. [11]. Valbuena D, Verburg PH, Veldkamp A, Bregt AK, Ligtenberg A. Effects of farmers’ decisions on the landscape structure of a Dutch rural region: An agent-based approach. Landscape and Urban Planning. 2010 Aug 30;97(2):98-110. [12]. Wossen T, Berger T, Haile MG, Troost C. Impacts of climate variability and food price volatility on household income and food security of farm households in East and West Africa. Agricultural systems. 2018 Jun 1;163:7-15. [13]. Zheng C, Liu Y, Bluemling B, Chen J, Mol AP. Modeling the environmental behavior and performance of livestock farmers in China: An ABM approach. Agricultural systems. 2013 Nov 1;122:60-72. [14]. Murray-Rust D, Robinson DT, Guillem E, Karali E, Rounsevell M. An open framework for agent based modelling of agricultural land use change. Environmental modelling & software. 2014 Nov 1;61:19-38. [15]. Akhbari M, Grigg NS. Managing water resources conflicts: modelling behavior in a decision tool. Water resources management. 2015 Nov 1;29(14):5201-16. [16]. Sobhani AA. Simulating the behavior of users in water application using an Agent-Based Model. New Researches in Management and Accounting. 2017;21:49-56. [Persian] [17]. Anbari MJ, Zarghami MZ. An Agent-Based Model to improve groundwater resources conditions with a participatory approach in the Shabestar-Sofian Plain, Iran. Iran-Water Resources Research. 2019;15(2):73-87. [Persian] [18]. Najjar Ghabel S, Zarghami MZ, Akhbari M, Nadiri A. Groundwater management in Ardabil Plain using Agent-Based Modeling. Iran-Water Resources Research. 2019;15(3):1-16. [Persian] [19]. Gilbert N. Agent-based models. Sage; 2008. [20]. Ferber J, Weiss G. Multi-agent systems: an introduction to distributed artificial intelligence. Reading: Addison-Wesley; 1999 Feb 25. [21]. Ghorbani A, Bots P, Dignum V, Dijkema G. MAIA: a framework for developing agent-based social simulations. Journal of Artificial Societies and Social Simulation. 2013 Mar 31;16(2):9. [22]. Ostrom E. Understanding institutional diversity Princeton University press. New Jersey. 2005:393-432. [23]. Ostrom E, Gardner R, Walker J, Walker J. Rules, games, and common-pool resources. University of Michigan Press; 1994. [24]. Ostrom E. A diagnostic approach for going beyond panaceas. Proceedings of the national Academy of sciences. 2007 Sep 25;104(39):15181-7. [25]. Castella JC, Trung NH, Boissau S. Participatory simulation of land-use changes in the northern mountains of Vietnam: the combined use of an agent-based model, a role-playing game, and a geographic information system. Ecology and Society. 2005;10(1):1-32. [26]. Mialhe F, Becu N, Gunnell Y. An agent-based model for analyzing land use dynamics in response to farmer behaviour and environmental change in the Pampanga delta (Philippines). Agriculture, ecosystems & environment. 2012 Oct 15;161:55-69. [27]. Valbuena D, Bregt AK, McAlpine C, Verburg PH, Seabrook L. An agent-based approach to explore the effect of voluntary mechanisms on land use change: A case in rural Queensland, Australia. Journal of environmental management. 2010 Dec 1;91(12):2615-25. [28]. Zhang H, Zeng Y, Jin X, Shu B, Zhou Y, Yang X. Simulating multi-objective land use optimization allocation using Multi-agent system—A case study in Changsha, China. Ecological modelling. 2016 Jan 24;320:334-47. [29]. Bellaubi F, Pahl-Wostl C. Corruption risks, management practices, and performance in water service delivery in Kenya and Ghana: an agent-based model. Ecology and Society. 2017 Apr 18;22(2). [30]. Moreno JL. Sociometry, experimental method and the science of society. [31]. An L. Modeling human decisions in coupled human and natural systems: Review of agent-based models. Ecological Modelling. 2012 Mar 24;229:25-36. [32]. Mena CF, Walsh SJ, Frizzelle BG, Xiaozheng Y, Malanson GP. Land use change on household farms in the Ecuadorian Amazon: Design and implementation of an agent-based model. Applied Geography. 2011 Jan 1;31(1):210-22. [33]. Ali AM, Shafiee ME, Berglund EZ. Agent-based modeling to simulate the dynamics of urban water supply: Climate, population growth, and water shortages. Sustainable Cities and Society. 2017 Jan 1;28:420-34. [34]. Ciampolini A, Lamma E, Mello P, Toni F, Torroni P. Cooperation and competition in ALIAS: a logic framework for agents that negotiate. Annals of Mathematics and Artificial Intelligence. 2003 Jan 1;37(1-2):65-91. [35]. Janssen M, Ostrom E. Empirically based, agent-based models. Ecology and society. 2006 Dec 18;11(2). [36]. Sun Z, Müller D. A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models. Environmental modelling & software. 2013 Jul 1;45:15-28. [37]. Bert FE, Podestá GP, Rovere SL, Menéndez ÁN, North M, Tatara E, et al. An agent based model to simulate structural and land use changes in agricultural systems of the argentine pampas. Ecological Modelling. 2011 Oct 10;222(19):3486-99. [38]. Neitsch SL, Arnold JG, Kiniry JR, Williams JR. Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute; 2011. [39]. Steduto P, Hsiao TC, Fereres E, Raes D. Crop yield response to water. Rome: fao; 2012. [40]. Thornthwaite CW. An approach toward a rational classification of climate. Geographical review. 1948 Jan 1;38(1):55-94. [41]. Kim I, Poppenborg P, Park SJ, Koellner T. Simulation of agricultural land-use changes and ecosystem services in a mountainous agricultural region using an agent-based model (ABM). Development of integrated modeling framework of land use changes and ecosystem services in mountainous watersheds. 2017 Mar 29:109. [42]. Iran Meteorological Organization, Ministry of Agriculture-Jihad. National Water Document of Iran; Net irrigation water demand for arable farming and fruit trees in Iran; 1999. [Persian] [43]. Vakili Fard HR, Khoshnoud M, Foroughnezhad H, Osoulian M. Agent-Based Modeling in financial markets. Investigation Science. 2014;12:139-158. [Persian] [44]. Crooks AT, Castle CJ. The integration of agent-based modelling and geographical information for geospatial simulation. InAgent-based models of geographical systems 2012 (pp. 219-251). Springer, Dordrecht. [45]. Mena CF, Walsh SJ, Frizzelle BG, Xiaozheng Y, Malanson GP. Land use change on household farms in the Ecuadorian Amazon: Design and implementation of an agent-based model. Applied Geography. 2011 Jan 1;31(1):210-22. [46]. Valbuena D, Verburg PH, Bregt AK, Ligtenberg A. An agent-based approach to model land-use change at a regional scale. Landscape ecology. 2010 Feb 1;25(2):185-99. [47]. Swinerd C, McNaught KR. Design classes for hybrid simulations involving agent-based and system dynamics models. Simulation Modelling Practice and Theory. 2012 Jun 1;25:118-33. [48]. Yu Q, Wu W, Chen Y, Yang P, Meng C, Zhou Q, et al. Model application of an agent-based model for simulating crop pattern dynamics at regional scale based on MATLAB. Transactions of the Chinese Society of Agricultural Engineering. 2014 Jan 1;30(12):105-14. [49]. Ligmann-Zielinska A. Spatially-explicit sensitivity analysis of an agent-based model of land use change. International Journal of Geographical Information Science. 2013 Sep 1;27(9):1764-81. | ||
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